Mar Rodríguez‐Girondo

The paper introduces a penalized reduced rank regression model for multi-outcome survival data, finding a common metabolic risk score associated with age-related diseases using UK Biobank data.

The paper introduces a new inverse probability of selection weighted Cox model to correct for outcome-dependent sampling bias in survival analysis, demonstrating its effectiveness through simulations and real datasets.

CAL-Leiden is a co-segregation model for BRCA1, BRCA2, and PALB2 variant classification, integrating population data and cancer types to improve pathogenicity assessment.

The paper introduces the AccelerAge framework, a statistical method for predicting biological age using time-to-event data, and evaluates it against existing predictors.

This paper examines the assumptions of cross-sectional biological age predictors and shows that a key assumption is untestable and can lead to unreliable results.

This study shows that having more long-lived ancestors is linked to longer healthspan and better mid-life metabolomic profiles in families.

The paper examines whether the survival advantage of offspring from long-lived parents is genetic or environmental, finding a genetic component that persists beyond age 5.

The paper identifies heritable longevity carriers using a family score and shows that longevity is transmitted across generations when at least 20% of relatives are long-lived.

The paper shows that longevity as top 10% survivors is a quantitative genetic trait, with a 31% survival advantage in families with long-lived relatives.